The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/cb6b5bc6-d50a-4efc-863d-d756cdc698e5

Patil, Akshay; Garcia Sanchez, Clara (2025): Dataset - A Comparative Hydrodynamic Characterization of the Flow Through Regular and Stochastically Generated Synthetic Coral Reefs Over Flat Topography. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/cb6b5bc6-d50a-4efc-863d-d756cdc698e5.v1

Dataset

• Civil Engineering
• Oceanography
• Other Environment
• Earth Sciences
• Engineering
• Environment

Canopy Turbulence, Coastal Dynamics, Coral Reefs, Direct Numerical Simulations, Fluid Dynamics

CC BY-ND 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Akshay Patil , Clara Garcia Sanchez

This repository contains the dataset to reproduce the figures in the conference proceedings for the manuscript titled "A Comparative Hydrodynamic Characterization of the Flow-Through Regular and Stochastically Generated Synthetic Coral Reefs Over Flat Topography" at the Coastal Dynamics 2025, Portugal meeting. This work aims to better understand the effect of regularly arranged coral reefs versus stochastically generated coral reefs generated using a variety of coral species. Specifically, the goal here is to ascertain how well prototypical coral geometries perform against morphologically complex collections of coral reefs. This dataset contains the reduced profiles used to generate the figures in the manuscript. Specifically, includes the velocity and TKE dissipation profiles, along with the vertical grid used to plot the figures. A set of Python scripts is also included to reproduce the figures.

• 2025-01-21 first online, published, posted

4TU.ResearchData

Numpy arrays, python script

• https://github.com/AkshayPatil1994/PatilGarcia-Sanchez_CoastalDynamics2025

• Multi-Fidelity Computational Modelling of Environmental Fluid Systems (grant code 2024/ENW/01763969) SURF Cooperative Supplemented by the Dutch Research Council (NWO)

TU Delft, Faculty of Architecture and the Built Environment, Department of Urbanism, Section Urban Data Science, 3DGeoinformation Research Group